Correlation Between NISSAN CHEMICAL and Mitsubishi Gas
Can any of the company-specific risk be diversified away by investing in both NISSAN CHEMICAL and Mitsubishi Gas at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining NISSAN CHEMICAL and Mitsubishi Gas into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NISSAN CHEMICAL IND and Mitsubishi Gas Chemical, you can compare the effects of market volatilities on NISSAN CHEMICAL and Mitsubishi Gas and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in NISSAN CHEMICAL with a short position of Mitsubishi Gas. Check out your portfolio center. Please also check ongoing floating volatility patterns of NISSAN CHEMICAL and Mitsubishi Gas.
Diversification Opportunities for NISSAN CHEMICAL and Mitsubishi Gas
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between NISSAN and Mitsubishi is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding NISSAN CHEMICAL IND and Mitsubishi Gas Chemical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mitsubishi Gas Chemical and NISSAN CHEMICAL is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on NISSAN CHEMICAL IND are associated (or correlated) with Mitsubishi Gas. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mitsubishi Gas Chemical has no effect on the direction of NISSAN CHEMICAL i.e., NISSAN CHEMICAL and Mitsubishi Gas go up and down completely randomly.
Pair Corralation between NISSAN CHEMICAL and Mitsubishi Gas
Assuming the 90 days trading horizon NISSAN CHEMICAL IND is expected to generate 0.75 times more return on investment than Mitsubishi Gas. However, NISSAN CHEMICAL IND is 1.33 times less risky than Mitsubishi Gas. It trades about 0.09 of its potential returns per unit of risk. Mitsubishi Gas Chemical is currently generating about 0.06 per unit of risk. If you would invest 3,080 in NISSAN CHEMICAL IND on September 3, 2024 and sell it today you would earn a total of 180.00 from holding NISSAN CHEMICAL IND or generate 5.84% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
NISSAN CHEMICAL IND vs. Mitsubishi Gas Chemical
Performance |
Timeline |
NISSAN CHEMICAL IND |
Mitsubishi Gas Chemical |
NISSAN CHEMICAL and Mitsubishi Gas Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with NISSAN CHEMICAL and Mitsubishi Gas
The main advantage of trading using opposite NISSAN CHEMICAL and Mitsubishi Gas positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NISSAN CHEMICAL position performs unexpectedly, Mitsubishi Gas can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Mitsubishi Gas will offset losses from the drop in Mitsubishi Gas' long position.NISSAN CHEMICAL vs. TOTAL GABON | NISSAN CHEMICAL vs. Walgreens Boots Alliance | NISSAN CHEMICAL vs. Peak Resources Limited |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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